Text Mining: Classification, Clustering, and Applications by Ashok Srivastava, Mehran Sahami

Text Mining: Classification, Clustering, and Applications Ashok Srivastava, Mehran Sahami ebook
Format: pdf
Page: 308
Publisher: Chapman & Hall
ISBN: 1420059408, 9781420059403

In-depth discussions are presented on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation. Here are some of the open source NLP and machine learning tools for text mining, information extraction, text classification, clustering, approximate string matching, language parsing and tagging, and more. Survey of Text Mining II: Clustering , Classification, and Retrieval . Issues relating to interoperability, information silos and access restrictions are limiting the uptake, degree of automation and potential application areas of text mining. This second volume continues to survey the evolving field of text mining - the application of techniques of machine learning, in conjunction with natural language processing, information extraction and algebraic/mathematical approaches, to computational information retrieval. Srivastava is the author of many research articles on data mining, machine learning and text mining, and has edited the book, “Text Mining: Classification, Clustering, and Applications” (with Mehran Sahami, 2009). Download Survey of Text Mining II: Clustering, Classification, and Retrieval - Free chm, pdf ebooks rapidshare download, ebook torrents bittorrent download. Text Mining and its Applications to Intelligence, CRM and Knowledge Management (Advances in Management Information) - Alessandro Zanasi (Editor), WIT Press, 2007. And Lafferty, J.D., “Topic Models”, Text mining: classification, clustering, and applications., 2009, pp. Uncertain Spatio-temporal Applications.- Uncertain Representations and Applications in Sensor Networks.- OLAP over .